Jill M Morrison1, Celia V Laur2, Heather H Keller3,4. 1. Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada. jill.morrison@uwaterloo.ca. 2. School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada. 3. Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada. 4. Schlegel-UW Research Institute for Aging, Waterloo, ON, Canada.
Abstract
BACKGROUND/ OBJECTIVES: Screening for nutrition risk in community-dwelling older adults increases the likelihood of early intervention to improve nutritional status, with short screening tools preferred. SCREEN-II-AB is a valid 8-item tool. The current study determines whether SCREEN-III, a proposed 3-item version, adequately classifies nutrition risk in comparison. SUBJECTS/ METHODS: Baseline data from the Canadian Longitudinal Study on Aging were used. Seventy-two percent (n = 24,456) of eligible participants (>55 years, complete SCREEN-II-AB) were included. Sensitivity and specificity of various SCREEN-III values compared with SCREEN-II-AB risk determined a nutrition risk cut-point and the proportion misclassified (False[-]) was calculated. Construct validity was tested against a composite variable summarizing outcomes associated with nutrition risk (e.g., self-reported health, hospitalization) using logistic regression adjusted for individual factors (e.g., marital status). RESULTS: A SCREEN-III cut-point of <22 performed best on sensitivity (0.83 [95% CI = 0.82, 0.84]) and specificity (0.73 [95% CI = 0.72, 0.74]) compared to SCREEN-II-AB (Cramer's V = 0.53). Of those at-risk using SCREEN-II-AB, 16.7% were misclassified as False(-) by SCREEN-III. The False(-) group did not differ significantly from the True(-) group. Based on SCREEN-III, 45.3% of individuals were at nutrition risk, 44% of whom reported the outcome composite. SCREEN-III nutrition risk was associated with greater odds of the outcome composite compared to those not at-risk (OR = 1.40, 95% CI = 1.33, 1.48, P < 0.0001). CONCLUSION: The proposed version of SCREEN-III demonstrated construct validity, but misclassification of risk may be problematic; further validation of a 3-item version is recommended.
BACKGROUND/ OBJECTIVES: Screening for nutrition risk in community-dwelling older adults increases the likelihood of early intervention to improve nutritional status, with short screening tools preferred. SCREEN-II-AB is a valid 8-item tool. The current study determines whether SCREEN-III, a proposed 3-item version, adequately classifies nutrition risk in comparison. SUBJECTS/ METHODS: Baseline data from the Canadian Longitudinal Study on Aging were used. Seventy-two percent (n = 24,456) of eligible participants (>55 years, complete SCREEN-II-AB) were included. Sensitivity and specificity of various SCREEN-III values compared with SCREEN-II-AB risk determined a nutrition risk cut-point and the proportion misclassified (False[-]) was calculated. Construct validity was tested against a composite variable summarizing outcomes associated with nutrition risk (e.g., self-reported health, hospitalization) using logistic regression adjusted for individual factors (e.g., marital status). RESULTS: A SCREEN-III cut-point of <22 performed best on sensitivity (0.83 [95% CI = 0.82, 0.84]) and specificity (0.73 [95% CI = 0.72, 0.74]) compared to SCREEN-II-AB (Cramer's V = 0.53). Of those at-risk using SCREEN-II-AB, 16.7% were misclassified as False(-) by SCREEN-III. The False(-) group did not differ significantly from the True(-) group. Based on SCREEN-III, 45.3% of individuals were at nutrition risk, 44% of whom reported the outcome composite. SCREEN-III nutrition risk was associated with greater odds of the outcome composite compared to those not at-risk (OR = 1.40, 95% CI = 1.33, 1.48, P < 0.0001). CONCLUSION: The proposed version of SCREEN-III demonstrated construct validity, but misclassification of risk may be problematic; further validation of a 3-item version is recommended.
Authors: Rachel Jl Prowse; Sarah A Richmond; Sarah Carsley; Heather Manson; Brent Moloughney Journal: Public Health Nutr Date: 2020-07-03 Impact factor: 4.022
Authors: Marla K Beauchamp; Brenda Vrkljan; Renata Kirkwood; Elisabeth Vesnaver; Luciana G Macedo; Heather Keller; Janie Astephen-Wilson; Nazmul Sohel; Tara Noble; Nicholas Dietrich; Paula Gardner; K Bruce Newbold; Darren Scott Journal: BMJ Open Date: 2021-12-16 Impact factor: 2.692